Google Professional Cloud DevOps Engineer - GCP - Exams
Description
This course is a specialized online training program tailored for individuals aiming to excel in the Google Professional Cloud DevOps Engineer certification. This course provides a series of comprehensive mock exams designed to replicate the environment and format of the actual GCP certification exam, offering learners an authentic exam experience.
This course delves deep into the essential topics and skills required for a DevOps engineer specializing in the Google Cloud Platform (GCP). It covers areas such as CI/CD pipelines, monitoring and logging, infrastructure as code, and site reliability engineering, all within the context of GCP services and tools. The course's structure is aligned with the official exam guide, ensuring that all relevant domains are thoroughly addressed.
Each mock exam includes a variety of question formats, including scenario-based and multiple-choice questions, simulating the types of challenges that candidates will face in the actual exam. Detailed explanations and insights accompany each question, providing learners with a deeper understanding of the underlying principles and best practices in cloud DevOps on GCP.
This course is ideal for existing IT professionals, cloud engineers, and system administrators seeking to validate their expertise in managing and optimizing GCP services. It's also beneficial for those transitioning into DevOps roles and looking to gain a reputable certification in the field. By the end of this course, learners will have enhanced their test-taking skills and gained the confidence needed to tackle the Google Professional Cloud DevOps Engineer certification exam successfully.
Is it possible to take the practice test more than once?
Certainly, you are allowed to attempt each practice test multiple times. Upon completion of the practice test, your final outcome will be displayed. With every attempt, the sequence of questions and answers will be randomized.
Is there a time restriction for the practice tests?
Indeed, each test comes with a time constraint of 120 seconds for each question.
What score is required?
The target achievement threshold for each practice test is to achieve at least 70% correct answers.
Do the questions have explanations?
Yes, all questions have explanations for each answer.
Am I granted access to my responses?
Absolutely, you have the opportunity to review all the answers you submitted and ascertain which ones were correct and which ones were not.
Are the questions updated regularly?
Indeed, the questions are routinely updated to ensure the best learning experience.
Additional Note: It is strongly recommended that you take these exams multiple times until you consistently score 90% or higher on each test. Take the challenge without hesitation and start your journey today. Good luck!
Who this course is for:
- everyone who wants to take the Google Professional Cloud DevOps Engineer exam
- everyone who wants to become a Google Professional Cloud DevOps Engineer
- everyone who wants to prepare for an interview with Google Cloud
- everyone who wants to work with Google Cloud
Instructor
EN
Python Developer/AI Enthusiast/Data Scientist/Stockbroker
Enthusiast of new technologies, particularly in the areas of artificial intelligence, the Python language, big data and cloud solutions. Graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science and Big Data specialization. Master's degree graduate in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics. Since 2015, a licensed Securities Broker with the right to provide investment advisory services (license number 3073). Lecturer at the GPW Foundation, conducting training for investors in the field of technical analysis, behavioral finance, and principles of managing a portfolio of financial instruments.
Founder at e-smartdata
PL
Data Scientist, Securities Broker
Jestem miłośnikiem nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python big data oraz rozwiązań chmurowych. Posiadam stopień absolwenta podyplomowych studiów na kierunku Informatyka, specjalizacja Big Data w Polsko-Japońskiej Akademii Technik Komputerowych oraz magistra z Matematyki Finansowej i Aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego. Od 2015 roku posiadam licencję Maklera Papierów Wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego (nr 3073). Jestem również wykładowcą w Fundacji GPW prowadzącym szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych. Mam doświadczenie w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką. Moje główne obszary zainteresowań to język Python, sztuczna inteligencja, web development oraz rynki finansowe.
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